Allocation of energy resources for power generation in India: Business as usual and energy efficiency

doi:10.1016/j.enpol.2009.10.058

Energy Policy

Volume 38, Issue 2, February 2010, Pages 1059-1066

https://doi.org/10.1016/j.enpol.2009.10.058 Get rights and content

Abstract

This paper deals with MARKAL allocations for various energy sources, in India, for Business As Usual (BAU) scenario and for the case of exploitation of energy saving potential in various sectors of economy. In the BAU scenario, the electrical energy requirement will raise up to 5000 bKwh units per year or 752 GW of installed capacity with major consumers being in the industry, domestic and service sectors. This demand can be met by a mix of coal, hydro, nuclear and wind technologies. Other reneawbles i.e. solar and biomass will start contributing from the year 2040 onwards. By full exploitation of energy saving potential, the annual electrical energy demand gets reduced to 3061 bKwh (or 458 GW), a reduction of 38.9%.The green house gas emissions reduce correspondingly. In this scenario, market allocations for coal, gas and large hydro become stagnant after the year 2015.

Introduction

During the past two decades, the demand for electricity in India has grown at an average rate of 6.5%. The capacity for power generation has not been able to keep pace and could grow only at the rate of 4.4% between the years 1990 and 2005. Coal is the main energy source followed by large hydro and gas. Conventional coal technology, however, do not offer high fuel efficiency. As a result, more carbon is burnt in generating one unit of electricity

Forecasting future energy demand and optimum allocations of energy resources are necessary requirement for a rational energy policy. Energy demand projections based on the GDP have been reported by Dincer and Dost (1997). Galli (1998) estimated the relationship between energy intensity and income levels by forecasting long term energy demand in Asian emerging countries. Erdogam and Dalh (1997) investigated the impact of income, price and population on the aggregate, industrial, manufacture and mining sectors of energy in Turkey. Hunt et al. (2003) presented UK energy demand for various sectors underlying trends and seasonality. Crompton and Wu (2005) presented energy consumption in China: past trends and future directions. Mirasgedis et al. (2006) presented a model for mid-term electricity demand forecasting incorporating weather influences. Shiu and Lam (2004) have studied electricity consumption and economic growth in china. Wolde-Rufael (2006) has estimated electricity consumption and economic growth: a time series experience for 17 African countries. Yoo (2005) studied electricity consumption and economic growth: evidence from Korea. Nasr et al. (2000) studied econometric modeling for electricity consumption in post-war Lebanon.

A number of forecast studies have also been conducted in India. Ghosh (2002) presented electricity consumption patterns related to economic growth in India. Population growth and oil prices are projected by Majumdar and Parikh (1996). In a report by planning commission of India (PC, 2006), future electricity demand has been projected on the basis of elasticity with respect to GDP.TERI (2006) has assumed various GDP growth scenarios and used regression model to project future energy and electricity demand.

Most of these studies consider GDP and population and associated elasticities for projecting future energy demand. In a paper Mallah and Bansal (2009a), had considered a time series to forecast sectoral GDPs, number of consumers in various sectors and price indices of electricity. These data of sectoral GDPs was used in an econometric model to forecast future electricity demand. The econometric model was based on logarithmic linearity. The results of the model had shown that in the BAU scenario, the demand–supply gap in the year 2045 may rise up to 70%. In another study (Mallah and Bansal, 2009b), it was shown that this demand–supply gap could be reduced to 40%, if the energy conservation potential is fully exploited. This remaining gap can be filled by a renewable energy mix of hydro, wind, solar and biomass technologies.

The mix of energy supply is, however, not an optimum solution. To find the optimum solution of energy mix a reference energy system (RES) has been developed for the Indian power sector.

Optimum resource allocations and corresponding economic costs can be obtained by MARKAL model. In this paper, MARKAL simulations have been performed for the cases:

•
Business as usual (BAU): This relates to cost minimization with due consideration of investment costs, O&M costs, fuel costs for all the technologies and associated parametric constraints.
•
Energy efficiency: Considering the effect of introducing energy conservation potential in different sectors of economy.

The corresponding CO₂ emissions have also been estimated in the process.

Section snippets

Reference energy system of Indian power sector

Reference energy system is a way of representing the activities and relationships of an energy system, depicting energy demands, energy conversion technologies, fuel mixes, and the resources required to satisfy energy demands (Meier, 1984). Most convenient way of expressing the RES is through its pictorial format that is a networked diagram indicating energy flows and the associated process parameters (e.g. efficiencies) of technologies employed in various stages of the energy system. Building

MARKAL model development

The use of scenarios guides the actual analysis of technological futures and assists in understanding how complex systems may evolve. Scenarios are internally consistent depictions of how the future may unfold, given assumptions about economic, social, political and technological developments as well as consumer preferences (Manne and Wene, 1992). Scenarios explore plausible futures by using a model or models to generate an outcome (or set of alternative outcomes) consistent with a set of

Base case results (BAU)

The base case results presented in this section are generated running the base case scenario from 2005 to 2045. Fig. 2 shows the market allocation of various electricity generation technologies. The total electricity generation increases very fast from base year 2005–2015 with a growth rate of 10% annually. For the period 2015–2030, the growth rate slows down. The annual increase is only 1.4%. After the year 2030, the average annual growth rate increases again and becomes 6%.

It is observed that

Conclusions

MARKAL simulations of energy resources for Indian electrical power supply have been performed for the case of BAU and energy conservation. In the case of BAU scenario, the electrical energy demand becomes 5000 bkWh in the year 2045 as compared to 600 bkWh for the base year of 2005. The corresponding CO₂ emissions become 2.3 billion tonnes in the year 2045. Because considerable energy saving potential, about 23%, exists in Indian economic sectors, allocations have been made for full as well as

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Allocation of energy resources for power generation in India: Business as usual and energy efficiency

Abstract

Introduction

Section snippets

Reference energy system of Indian power sector

MARKAL model development

Base case results (BAU)

Conclusions

Energy Economics

Energy Policy

Energy Economics

Energy Policy

Energy

Energy Economics

Energy Policy

Energy Policy

Energy Policy

Energy and GDP

International Journal of Energy Research